#193 Liberty (10-9)

avg: 966.5  •  sd: 65.55  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
86 Duke Loss 4-13 798.98 Feb 3rd Mid Atlantic Warmup 2018
194 George Washington Loss 8-11 598.82 Feb 3rd Mid Atlantic Warmup 2018
115 Villanova Loss 4-13 676.67 Feb 3rd Mid Atlantic Warmup 2018
250 Maryland-Baltimore County Win 12-7 1289.21 Feb 3rd Mid Atlantic Warmup 2018
234 Haverford Loss 10-11 682.5 Feb 4th Mid Atlantic Warmup 2018
161 Boston University Loss 8-15 522.99 Feb 4th Mid Atlantic Warmup 2018
107 Rutgers Loss 7-15 714.37 Feb 4th Mid Atlantic Warmup 2018
223 High Point Win 7-5 1191.24 Feb 17th Chucktown Throwdown XV
116 Appalachian State Loss 2-9 674.46 Feb 17th Chucktown Throwdown XV
282 Wingate Win 6-5 787.96 Feb 17th Chucktown Throwdown XV
273 Wake Forest Win 9-4 1301.68 Feb 17th Chucktown Throwdown XV
252 Western Carolina Win 7-6 887.3 Feb 17th Chucktown Throwdown XV
249 North Greenville Win 13-0 1369.37 Feb 18th Chucktown Throwdown XV
303 Charleston Win 10-7 961.15 Feb 18th Chucktown Throwdown XV
122 Tennessee Loss 7-10 865.88 Feb 18th Chucktown Throwdown XV
291 Bentley Win 13-7 1171.22 Mar 31st New England Open 2018
92 Bowdoin Loss 6-13 767.81 Mar 31st New England Open 2018
161 Boston University Win 13-9 1506.36 Mar 31st New England Open 2018
314 Wentworth Institute of Technology Win 13-6 1130.99 Mar 31st New England Open 2018
**Blowout Eligible

FAQ

The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)